Research Society, 32(1), 19-26.
Chen, F.-L., Chen, Y.-C., & Kuo, J.-Y. (2010). Applying moving back-propagation neural network and moving fuzzy neuron network to predict the requirement of critical spare parts. Expert Systems
with Applications, 37(6), 4358-4367.
Chen, J.-X. (2011). Peer-estimation for multiple criteria ABC inventory classification. Computers &
Operations Research, 38(12), 1784-1791.
Chen, J.-X. (2012). Multiple criteria ABC inventory classification using two virtual items.
International Journal of Production Research, 50(6), 1702-1713.
Chen, Y., Li, K. W., Kilgour, D. M., & Hipel, K. W. (2008). A case-based distance model for multiple criteria ABC analysis. Computers & Operations Research, 35(3), 776-796.
Chen, Y., Li, K. W., Levy, J., Hipel, K. W., & Kilgour, D. M. (2008). A rough set approach to multiple criteria ABC analysis, Transactions on Rough Sets VIII (pp. 35-52), Springer.
Cheng, Y. H., & Tsao, H. L. (2010). Rolling stock maintenance strategy selection, spares parts estimation, and replacements‘ interval calculation. International Journal of Production
Economics, 128(1), 404-412.
Chu, C.-W., Liang, G.-S., & Liao, C.-T. (2008). Controlling inventory by combining ABC analysis and fuzzy classification. Computers & Industrial Engineering, 55(4), 841-851.
C-MORE, Spares Management Software (SMS), CMORE University of Toronto, Ver 2.00.0, 2013. Costantino, F., Di Gravio, G., & Tronci, M. (2013). Multi-echelon, multi-indenture spare parts
inventory control subject to system availability and budget constraints. Reliability Engineering &
System Safety, 119, 95-101.
de Smidt-Destombes, K. S., Van der Heijden, M. C., & Van Harten, A. (2004). On the availability of a k-out-of-N system given limited spares and repair capacity under a condition based maintenance strategy. Reliability Engineering & System Safety, 83(3), 287-300.
de Smidt-Destombes, K. S., Van der Heijden, M. C., & Van Harten, A. (2006). On the interaction between maintenance, spare part inventories and repair capacity for a k-out-of-N system with wear-out. European Journal of Operational Research, 174(1), 182-200.
de Smidt-Destombes, K. S., Van der Heijden, M. C., & Van Harten, A. (2007). Availability of k-out-of-N systems under block replacement sharing limited spares and repair capacity.
ACCEPTED MANUSCRIPT
de Smidt-Destombes, K. S., Van der Heijden, M. C., & Van Harten, A. (2009). Joint optimisation ofspare part inventory, maintenance frequency and repair capacity for k-out-of-N systems.
International Journal of Production Economics, 118(1), 260-268.
Dekker, R., Bloemhof, J., & Mallidis, I. (2012). Operations Research for green logistics–An overview of aspects, issues, contributions and challenges. European Journal of Operational Research, 219(3), 671-679.
Diaz, A., & Fu, M. C. (1997). Models for multi-echelon repairable item inventory systems with limited repair capacity. European Journal of Operational Research, 97(3), 480-492.
Digiesi, S., Mossa, G., & Rubino, S. (2015). A sustainable EOQ model for repairable spare parts under uncertain demand. IMA Journal of Management Mathematics, 26(2), 185-203.
Driessen, M., Arts, J., Van Houtum, G.J., Rustenburg J.W., & Huisman, B. (2015). Maintenance spare parts planning and control: A framework for control and agenda for future research. Production
Planning & Control: the Management of Operations, 26(5), 407-426.
Dubi, A. (2006). The Monte Carlo method and optimisation of spare parts in complex realistic scenarios. Paper presented at the RAMS'06 Annual Reliability and Maintainability Symposium. Duffuaa, S., Ben-Daya, M., Al-Sultan, K., & Andijani, A. (2001). A generic conceptual simulation
model for maintenance systems. Journal of Quality in Maintenance Engineering, 7(3), 207-219. Eaves, A. H. C. (2002). Forecasting for the ordering and stock-holding of consumable spare parts.
Unpublished PhD thesis, Lancaster University.
Eaves, A., & Kingsman, B. (2004). Forecasting for the ordering and stock-holding of spare parts.
Journal of the Operational Research Society, 55(4), 431-437.
Eren, B., & Erol, S. (2015). The Proposal of Demand Estimation of Repairable Items for the Weapon Systems During the Initial Provisioning Period: F-16 Case Study. In Military Logistics (pp. 43-71). Springer International Publishing.
Exton, T., & Labib, A. (2002). Spare parts decision analysis–The missing link in CMMSs (Part II).
Journal of Maintenance & Asset Management, 17(1), 14-21.
Fildes, R. (1992). The evaluation of extrapolative forecasting methods. International Journal of
Forecasting, 8(1), 81-98.
Fildes, R., Goodwin, P., Lawrence, M., & Nikolopoulos, K. (2009). Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting, 25(1), 3-23.
ACCEPTED MANUSCRIPT
Fleischmann, M., Van Nunen, J. A., & Gräve, B. (2003). Integrating closed-loop supply chains andspare-parts management at IBM. Interfaces, 33(6), 44-56.
Flores, B. E., & Clay Whybark, D. C. (1986). Multiple criteria ABC analysis. International Journal of
Operations & Production Management, 6(3), 38-46.
Flores, B. E., & Clay Whybark, D. C. (1987). Implementing multiple criteria ABC analysis. Journal of
Operations Management, 7(1), 79-85.
Flores, B. E., Olson, D. L., & Dorai, V. (1992). Management of multicriteria inventory classification.
Mathematical and Computer Modelling, 16(12), 71-82.
Foote, B. L. (1995). On the implementation of a control-based forecasting system for aircraft spare parts procurement. IIE transactions, 27(2), 210-216.
Fortuin, L. (1980). The all-time requirement of spare parts for service after sales-theoretical analysis and practical results. International Journal of Operations & Production Management, 1(1), 59-70.
Fortuin, L. (1981). Reduction of the all-time requirement for spare parts. International Journal of
Operations & Production Management, 2(1), 29-37.
Fortuin, L. (1984). Initial supply and re-order level of new service parts. European Journal of
Operational Research, 15(3), 310-319.
Fortuin, L., & Martin, H. (1999). Control of service parts. International Journal of Operations &
Production Management, 19(9), 950-971.
Frazzon, E. M., Israel, E., Albrecht, A., Pereira, C. E., & Hellingrath, B. (2014). Spare parts supply chains‘ operational planning using technical condition information from intelligent maintenance systems. Annual Reviews in Control, 38(1), 147-154.
Gallagher, T., Mitchke, M. D., & Rogers, M. C. (2005). Profiting from spare parts. The McKinsey
Quarterly, February 2005, http://www.werc.org/assets/1/workflow_staging/Publications/666.pdf
Ghobbar A.A., & Friend, C.H. (2002) Sources of intermittent demand for aircraft spare parts within airline operations. Journal of Air Transport Management, 8(4), 221-231.
Ghobbar, A. A., & Friend, C. H. (2003). Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model. Computers & Operations Research, 30(14), 2097-2114.
Ghodrati, B. (2005). Reliability and Operational Environment Based Spare Parts Planning. Lulea University of Technology, Unpublished PhD Thesis.
ACCEPTED MANUSCRIPT
Ghodrati, B., Benjevic, D., & Jardine, A. (2012),"Product support improvement by considering systemoperating environment", International Journal of Quality & Reliability Management, 29(4), 436 – 450.
Ghodrati, B., & Kumar, U. (2005) Reliability and operating environment-based spare parts estimation: a case study from Kiruna Mine, Sweden. Journal of Quality in Maintenance Engineering, 11(2), 169-84.
Ghodrati, B. (2006). Weibull and exponential renewal models in spare parts estimation: a comparison.
International Journal of Performability Engineering, 2(2), 135-47.
Ghodrati, B., Ahmadi, A., & Galar, D. (2013). Spare parts estimation for machine availability improvement addressing its reliability and operating environment- case study. International
Journal of Reliability, Quality and Safety Engineering, 20(3), 134005 (15 pages).
Gilliland M. (2002). Is forecasting a waste of time? Supply Chain Management Review, 6(4), 16-23. Gross, D., Miller, D., & Soland, R. (1985). On some common interests among reliability, inventory
and queuing. IEEE Transactions on Reliability, 34 (3), 204-208.
Guide, V. D. R., & Srivastava, R. (1997). Repairable inventory theory: Models and applications.
European Journal of Operational Research, 102(1), 1-20.
Gutierrez, R. S., Solis, A. O., & Mukhopadhyay, S. (2008). Lumpy demand forecasting using neural networks. International Journal of Production Economics, 111(2), 409-420.
Guvenir, H. A., & Erel, E. (1998). Multicriteria inventory classification using a genetic algorithm.
European journal of Operational Research, 105(1), 29-37.
Hadi-Vencheh, A. (2010). An improvement to multiple criteria ABC inventory classification.
European Journal of Operational Research, 201(3), 962-965.
Hadi-Vencheh, A., & Mohamadghasemi, A. (2011). A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification. Expert Systems with Applications, 38(4), 3346-3352.
Haneveld, W. K., & Teunter, R. (1997). Optimal provisioning strategies for slow moving spare parts with small lead times. Journal of the Operational Research Society, 48(2), 184-194.
Hariga, M. (1996). Optimal EOQ models for deteriorating items with time-varying demand. Journal of
the Operational Research Society, 47(10), 1228-1246.
Hatefi, S., Torabi, S., & Bagheri, P. (2014). Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786.
ACCEPTED MANUSCRIPT
Heinecke, G., Syntetos, A., & Wang, W. (2013). Forecasting-based SKU classification. InternationalJournal of Production Economics, 143(2), 455-462.
Helmrich, M. J. R., Jans, R., Van den Heuvel, W., & Wagelmans, A. P. (2015). The economic lot-sizing problem with an emission capacity constraint. European Journal of Operational Research, 241(1), 50-62.
Hu, Q., Chakhar, S., Siraj, S., & Labib, A. (2017) Spare parts classification in industrial manufacturing using the dominance-based rough set approach, European Journal of Operational Research, http://dx.doi.org/10.1016/j.ejor.2017.04.040.
Hua, Z., & Zhang, B. (2006). A hybrid support vector machines and logistic regression approach for forecasting intermittent demand of spare parts. Applied Mathematics and Computation, 181(2), 1035-1048.
Hua, Z.S., Zhang, B., Yang, J., & Tan, D.S. (2007) A new approach of forecasting intermittent demand for spare parts inventories in the process industries. Journal of the Operational Research Society, 58(1), 52-61.
Huiskonen, J. (2001). Maintenance spare parts logistics: Special characteristics and strategic choices.
International Journal of Production Economics, 71(1), 125-133.
Hyndman RJ. (2006). Another look at forecast-accuracy metrics for intermittent demand. Foresight:
the International Journal of Applied Forecasting, 4, 43-46.
Inderfurth, K., & Kleber, R. (2013). An advanced heuristic for multiple-option spare parts procurement after end-of-production. Production and Operations Management, 22(1), 54-70.
Inderfurth, K., & Mukherjee, K. (2008). Decision support for spare parts acquisition in post product life cycle. Central European Journal of Operations Research, 16(1), 17-42.
Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L. K., & Young, T. (2010). Simulation in manufacturing and business: A review. European Journal of Operational Research, 203(1), 1-13. Jamshidi, H., & Jain, A. (2008). Multi-criteria ABC inventory classification: With exponential
smoothing weights. Journal of Global Business Issues, 2(1), 61-67.
Jaquette, D. L., & Osaki, S. (1972). Initial Provisioning of a Standby System with Deteriorating and Repairable Spares. IEEE Transactions on Reliability, 21(4), 245-247.
Jardine, A. K., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483-1510.
ACCEPTED MANUSCRIPT
Jardine, AKS. & Tsang, A.H.C. (2013) Maintenance replacement, and reliability: Theory andAppications, CRC Press.
Jin, T., & Liao, H. (2009). Spare parts inventory control considering stochastic growth of an installed base. Computers & Industrial Engineering, 56(1), 452-460.
Jin, T., & Tian, Y. (2012). Optimising reliability and service parts logistics for a time-varying installed base. European Journal of Operational Research, 218(1), 152-162.
Jin, T., Tian, Z., & Xie, M. (2015). A game-theoretical approach for optimising maintenance, spares and service capacity in performance contracting. International Journal of Production Economics, 161 (March 2015), 31-43.
Johnston, F. R., & Boylan, J. E. (1996). Forecasting for items with intermittent demand. Journal of the
Operational Research Society, 47(1), 113-121.
Jung, W. (1993). Recoverable inventory systems with time-varying demand. Production and Inventory
Management Journal, 34(1), 77-81.
Kabir, A. Z., & Farrash, S. (1996). Simulation of an integrated age replacement and spare provisioning policy using SLAM. Reliability Engineering & System Safety, 52(2), 129-138.
Kabir, G., & Hasin, M. A. (2012). Multiple criteria inventory classification using fuzzy analytic hierarchy process. International Journal of Industrial Engineering Computations, 3(2), 123-132. Kabir, G., & Hasin, M. A. (2013). Multi-criteria inventory classification through integration of fuzzy
analytic hierarchy process and artificial neural network. International Journal of Industrial and
Systems Engineering, 14(1), 74-103.
Kader, B., Sofiene, D., Nidhal, R., & Walid, E. (2015). Ecological and joint optimisation of preventive maintenance and spare parts inventories for an optimal production plan. IFAC-PapersOnLine, 48(3), 2139-2144.
Kennedy, W.J., Patterson, J. W, & Fredendall, L.D. (2002). An overview of recent literature on spare parts inventories. International Journal of Production Economics, 76(2), 201-215.
Khanra, S., Ghosh, S., & Chaudhuri, K. (2011). An EOQ model for a deteriorating item with time dependent quadratic demand under permissible delay in payment. Applied Mathematics and
Computation, 218(1), 1-9.
Khanra, S., Mandal, B., & Sarkar, B. (2013). An inventory model with time dependent demand and shortages under trade credit policy. Economic Modelling, 35, 349-355.